Cargando…
Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A Practical Review
Molecular and genomic properties are critical in selecting cancer treatments to target individual tumors, particularly for immunotherapy. However, the methods to assess such properties are expensive, time-consuming, and often not routinely performed. Applying machine learning to H&E images can p...
Autor principal: | Couture, Heather D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784641/ https://www.ncbi.nlm.nih.gov/pubmed/36556243 http://dx.doi.org/10.3390/jpm12122022 |
Ejemplares similares
-
Annotation-Free Deep Learning-Based Prediction of Thyroid Molecular Cancer Biomarker BRAF (V600E) from Cytological Slides
por: Wang, Ching-Wei, et al.
Publicado: (2023) -
Classification and mutation prediction based on histopathology H&E images in liver cancer using deep learning
por: Chen, Mingyu, et al.
Publicado: (2020) -
Deep learning-based transformation of H&E stained tissues into special stains
por: de Haan, Kevin, et al.
Publicado: (2021) -
Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology
por: Lee, Sung Hak, et al.
Publicado: (2022) -
Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images
por: Wen, Zhuoyu, et al.
Publicado: (2023)